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检索条件"机构=Key Laboratory of Data Engineering and Knowledge Engineering of MOE"
1144 条 记 录,以下是741-750 订阅
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Do we measure novelty when we analyze unusual combinations of cited references? A validation study of bibliometric novelty indicators based on F1000Prime data
arXiv
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arXiv 2019年
作者: Bornmann, Lutz Tekles, Alexander Zhang, Helena H. Ye, Fred Y. Division for Science and Innovation Studies Administrative Headquarters of the Max Planck Society Hofgartenstr. 8 Munich80539 Germany Ludwig-Maximilians-Universität Munich Department of Sociology Konradstr. 6 Munich80801 Germany Jiangsu Key Laboratory of Data Engineering Knowledge Service School of Information Management Nanjing University Nanjing210023 China Nanjing University Nanjing China University of Illinois Champaign United States
Lee, Walsh, and Wang (2015) – based on Uzzi, Mukherjee, Stringer, and Jones (2013) – and Wang, Veugelers, and Stephan (2017) proposed scores based on cited references (cited journals) data which can be used to measu...
来源: 评论
Deep Text Classification Can be Fooled
arXiv
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arXiv 2017年
作者: Liang, Bin Li, Hongcheng Su, Miaoqiang Bian, Pan Li, Xirong Shi, Wenchang School of Information Renmin University of China Beijing China Key laboratory of Data Engineering and Knowledge Engineering MOE Beijing China
In this paper, we present an effective method to craft text adversarial samples, revealing one important yet underestimated fact that DNN-based text classifiers are also prone to adversarial sample attack. Specificall... 详细信息
来源: 评论
NaCdSb: An Orthorhombic Zintl Phase with Exceptional Intrinsic Thermoelectric Performance
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Angewandte Chemie 2022年 第3期135卷
作者: Kai Guo Yuting Zhang Song Yuan Qinghang Tang Chen Lin Pengfei Luo Jiong Yang Shusheng Pan Li-Dong Zhao Guofeng Cheng Jiye Zhang Jun Luo School of Physics and Materials Science Guangzhou University Guangzhou 510006 China Research Center for Advanced Information Materials (CAIM) Huangpu Research & Graduate School of Guangzhou University Sino-Singapore Guangzhou Knowledge City Huangpu District Guangzhou 510555 China Contribution: Conceptualization (lead) Formal analysis (equal) Writing - original draft (lead) School of Materials Science and Engineering Shanghai University 99 Shangda Road Shanghai 200444 China Contribution: Data curation (equal) ​Investigation (equal) Validation (lead) Contribution: Data curation (lead) Formal analysis (equal) Materials Genome Institute Shanghai University 99 Shangda Road Shanghai 200444 China Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education and School of Physics and Technology Wuhan University Wuhan 430072 China Contribution: ​Investigation (equal) Contribution: ​Investigation (equal) Methodology (supporting) Contribution: ​Investigation (equal) Writing - review & editing (supporting) School of Materials Science and Engineering Beihang University Beijing 100191 China Contribution: Methodology (equal) Writing - review & editing (equal) Analysis & Testing Center for Inorganic Materials Shanghai Institute of Ceramics Chinese Academy of Sciences Shanghai 200050 China Contribution: Formal analysis (equal) ​Investigation (supporting) Contribution: Data curation (equal) Writing - review & editing (supporting) Contribution: Supervision (lead) Writing - review & editing (equal)
Many Zintl phases are promising thermoelectric materials owning to their features like narrow band gaps, multiband behaviors, ideal charge transport tunnels, and loosely bound cations. Herein we show a new Zintl phase... 详细信息
来源: 评论
A Novel Texture Generation Super Resolution Model
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Procedia Computer Science 2019年 162卷 924-931页
作者: Biao Li Yong Shi Sujuan Li Bo Wang Zhiquan Qi Jiabin Liu School of Economics and Management University of Chinese Academy of Sciences Beijing 101408 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China College of Information Science and Technology University of Nebraska at Omaha NE 68182 USA Department of Otology the First Affiliated Hospital of Zhengzhou University No. 1 eastern Jianshe road Zhengzhou Henan 450052 China School of Information Technology and Management University of International Business and Economics Beijing 100029 China Department of Computer Science and Engineering Texas A&M University TX 77843 USA
Recently, super-resolution methods pursue visual pleasant details attract more attention in academic circle. Unlike former accurate driving models, they leverage new losses measured the difference of features extracti... 详细信息
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Initializing convolutional filters with semantic features for text classification
Initializing convolutional filters with semantic features fo...
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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
作者: Li, Shen Zhao, Zhe Liu, Tao Hu, Renfen Du, Xiaoyong Institute of Chinese Information Processing Beijing Normal University China UltraPower-BNU Joint Laboratory for Artificial Intelligence Beijing Normal University China College of Chinese Language and Culture Beijing Normal University China School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China
Convolutional Neural Networks (CNNs) are widely used in NLP tasks. This paper presents a novel weight initialization method to improve the CNNs for text classification. Instead of randomly initializing the convolution... 详细信息
来源: 评论
s-LWSR: Super lightweight super-resolution network
arXiv
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arXiv 2019年
作者: Li, Biao Liu, Jiabin Wang, Bo Qi, Zhiquan Shi, Yong School of Economics and Management University of Chinese Academy of Sciences Beijing101408 China Research Center on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing100190 China School of Information Technology and Management University of International Business and Economics Beijing100029 China Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States College of Information Science and Technology University of Nebraska OmahaNE68182 United States
Deep learning (DL) architectures for super-resolution (SR) normally contain tremendous parameters, which has been regarded as the crucial advantage for obtaining satisfying performance. However, with the widespread us... 详细信息
来源: 评论
Investigating different syntactic context types and context representations for learning word embeddings
Investigating different syntactic context types and context ...
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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
作者: Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States
The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of cont... 详细信息
来源: 评论
Visual Feature Combination Approach for Zero-Shot Learning
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Ruan Jian Xue Bao/Journal of Software 2018年 29卷 16-29页
作者: Yang, Gang Liu, Jin-Lu Li, Xi-Rong Xu, Jie-Ping School of Information Renmin University of China Beijing100872 China Key Laboratory of Data Engineering and Knowledge Engineering Renmin University of China Beijing100872 China
Zero-Shot learning is an important research in the field of machine learning and image recognition. Zero-Shot learning methods normally use the semantic information among unseen classes and seen classes to transfer th... 详细信息
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Using improved particle swarm optimization to tune PID controllers in cooperative collision avoidance systems
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Frontiers of Information Technology & Electronic engineering 2017年 第9期18卷 1385-1395页
作者: Xing-chen WU Gui-he QIN Ming-hui SUN He YU Qian-yi XU College of Computer Science and Technology Jilin University Changchun 130012 China MOE Key Laboratory of Symbol Computation and Knowledge Engineering Changchun 130012 China Department of Measurement and Controlling Engineering Changchun University Changchun 130012 China
The introduction ofproportional-integral-dorivative (PID) controllers into cooperative collision avoidance systems (CCASs) has been hindered by difficulties in their optimization and by a lack of study of their ef... 详细信息
来源: 评论
Fast & scalable distributed set similarity joins for big data analytics  33
Fast & scalable distributed set similarity joins for big dat...
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33rd IEEE International Conference on data engineering, ICDE 2017
作者: Rong, Chuitian Lin, Chunbin Silva, Yasin N. Wang, Jianguo Lu, Wei Du, Xiaoyong Tianjin Polytechnic University China Arizona State University United States University of California San Diego United States Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Information Renmin University of China China
Set similarity join is an essential operation in big data analytics, e.g., data integration and data cleaning, that finds similar pairs from two collections of sets. To cope with the increasing scale of the data, dist... 详细信息
来源: 评论